2019: A year of buy-side transformation
2019: A time of buy-side transformation
A Bloomberg report
Preparing for a time of transformation
The buy side finds itself in a unique position in 2019.
The buy side finds itself in a unique position in 2019, one characterized by vivid contrasts in growth, opportunity and risk. Margin pressure remains significant, yet global AUM is on track to break records. Optimism seems warranted for most regions around the world, while the ongoing discussions on Brexit and heightened U.S.-China trade tensions cloud this forecast. Passive funds continue to race headlong toward zero fees, but smart beta products are growing at 30 percent annually.
Together, these dynamics are forcing the buy side to evolve at an ever-quickening pace. While some firms are focused on developing new operating models, others are considering how to find alpha with innovative applications of artificial intelligence and machine learning.
In this report, we explore these trends and tensions, offering insights from leaders across the buy side. Together, what these experts have to say sheds light on how investment managers can set priorities during 2019. This report also highlights some of the key questions investment managers will need to answer as the buy side enters a time of unprecedented change.
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2019 Outlook: Optimism tempered with political risk
Markets expect slower global growth in 2019, with U.S. growth holding steady while Europe and China decline.
The IMF confirmed this view in January, revising its global growth forecast down to 3.5 percent from 3.7 percent. Its U.S. growth prediction held at 2.5 percent, while the outlook for 19 nations that use the euro declined from 1.8 percent to 1.6 percent. Other analysts predict even lower numbers in the Eurozone — 1.4 percent in 2019 and 1.2 percent in 2020 — as well as slower growth in China of 6.1 percent due to the impact of U.S. tariffs.
This doesn’t mean the buy side will not be able to find good opportunities. According to State Street Global Advisors, U.S. equities are a potential bright spot. One factor that could increase their value is the results of the 2018 mid-terms. With Democrats in control of the House of Representatives, there is greater potential for infrastructure spending. Another factor is strong earnings growth for U.S. companies. One downside risk is increased rate hikes, but the Federal Reserve recently reduced its forecast to two key interest rate hikes in 2019 instead of three.
“We don’t see evidence the U.S. bull market is about to end,” says Richard Turnill, managing director, global chief investment strategist, BlackRock. “All our economic signals suggest above-trend growth in the U.S. over the next 12 months.”
Turnill notes three events that could trigger the end. One is traditional overheating, with accelerated inflation and the Fed stepping in to “stamp on the brakes.” The second is escalation of the trade war with China. The third is financial risk, or a bubble, caused by excesses within financial markets. But he sees little evidence of these.
“We’ve seen a series of volatility spikes through 2018 starting with bitcoin and extending to tech and emerging markets,” he says. “But the market rolls on. We don’t see conditions for the end of a bull market. But uncertainty is increasing. You want to have equities but focus on areas that are most resilient.”
Peaks and curves
After a difficult year, the fixed income market looks to continue moving toward the end of the credit cycle. In the U.S., rates are close to a cyclical peak and the yield curve is expected to flatten. Other countries are lagging behind simply because the U.S. began its recovery earlier. Further, structural constraints on U.S. growth and inflation — rising debt levels, an aging population and low productivity — will provide a cap on real rates according to State Street Global Advisors.
“There are a few factors in the U.S. that could drive 10-year treasury yields higher,” says Karen Ward, managing director and chief market strategist, EMEA, for J.P. Morgan Asset Management. “As people’s expectations about the distribution of inflation normalize, that will push term premium higher. If we see a resurgence in productivity in the U.S., that will drive the rate up as well. To see
4 percent, however, we need to see normalization elsewhere in the world.”
Investors seem relatively complacent. Perhaps because, in recent years, political risks haven’t had much impact on markets. This disconnect between global economic performance and dire politics in advanced economies is an alarm signal, according to Tina Fordham, managing director and chief global political analyst for Citi.
“As we enter a period of tightening in central bank policy with concerns about inflation and reasonably good growth, political risks will start to register more than in the past,” she says. “If you’ve been trading the last eight years, you could be forgiven for thinking political risks don’t matter. But quantitative easing has masked these risks.”
A crossroads for Europe
One of the biggest political risks is the seemingly never-ending uncertainty over Brexit. In the first quarter of 2019, U.K. Prime Minister Theresa May’s withdrawal deal was defeated in parliament three times by astonishing margins. With confidence faltering in May’s ability to deliver Brexit in any form, MPs took matters into their own hands through a series of votes to establish alternative courses of action – none of which gained a clear consensus.
In a bid to avoid the catastrophic “no deal” scenario that many fear, but no agreement on how to avoid it, May sought an extension to Article 50, then another. At the time of writing, the latest date for the U.K. to leave the EU was set at 31 October. May had opened up talks with the opposition Labour party in an attempt to agree a compromise deal that could pass through parliament. And Conservative cabinet members were lining up to challenge her leadership.
We are no closer to knowing how the U.K. will leave — whether under May’s deal, with a “softer” deal or with no deal at all — or, indeed, if it will leave at all, with many backing a second referendum or general election as the only way to break the deadlock.
The grinding uncertainty is prolonging the pain for the U.K. economy, with businesses and consumers on edge and investment intentions at their lowest level for eight years. That’s why news of the delay was welcomed with gritted teeth — more instability, without a guarantee of a better conclusion, is only marginally more appealing than a hard Brexit.
The six-month extension is seen by the Bank of England as too short to lift uncertainty for businesses and consumers, so it is unlikely to raise interest rates. In response to the delay announcement, the IMF cut its prediction for 2019 to growth of 1.2 percent from 1.5 percent — and even that is based on the assumption that the government will secure a deal.
“We have reached a nadir of negativity,” says Michele Gesualdi, Chief Investment Officer for Kairos Investment Management. “If you look at sterling and rates, there is a Brexit premium already built into these assets. Sterling is 20 to 30 percent cheaper than it should be in a normal scenario. If you look at rates, even more so. Clearly, the MPC wants to raise rates but is looking for a deal to do that.”
Despite MPs backing a move to prevent it, “no deal” remains the default legal position and the biggest danger on the horizon. The Bank of England has warned that the economy could shrink by 8 percent within a year, property prices could plunge almost a third and the pound could loses a quarter of its value.
Counting the cost
However — and whenever — the U.K. leaves, the Brexit vote has already caused considerable damage to the economy. There has been a steady departure of money and jobs from the City of London, which looks set to continue; without single-market access, U.K. banks will be subject to equivalence decisions like any other non-EU country. The housing market is down. A dramatic drop in immigration has left the hospitality, agriculture, construction and health industries grappling for workers. And the U.K.’s status as the European hub of choice is under threat.
With more months of limbo ahead, questions about everything from trade policy to immigration laws are choking hiring and investment decisions. Companies are spending millions of pounds on contingency measures and plotting overseas moves, while global banks are moving operations, assets and people to other European cities.
There is a domino effect. Global businesses that rely on the U.K. for trade and talent are on edge. Asian companies, who will face higher tariffs and costs post-Brexit, are forced to consider cutting their workforce and moving head offices out of
However, there have been moments of optimism amidst all the uncertainty. The round rejection of May’s initial deal led to a stabilization of the pound in response to a perceived increase in the likelihood of a softer Brexit — or of none at all, which investors would welcome. “This outcome is so dire for Brexit that the chances of a softer Brexit or even a second referendum may have risen,” said Stephen Jen, chief executive of Eurizon SLJ Capital, at the time.
Time is running out for May’s government to agree on an exit strategy that will satisfy both voters and the markets. The situation is changing by the day. As with the U.S. and China trade war, caution is warranted as we progress into 2019; we can only hope for an end to some of the uncertainty.
Volatility: The new normal for emerging markets?
For emerging market investors, 2018 was anything but calm.
Riven by the cross-currents of currency crises in Argentina and Turkey and trade friction between the U.S. and China, sentiment has shown signs of bottoming out and skepticism in these markets remains high. Of course, this also means that opportunities to invest in emerging markets are plentiful.
“That’s the story of our life in emerging markets,” says Dr. Mark Mobius, the founder of Mobius Capital Partners, who many consider to be the dean of emerging-market investing. “Money won’t start to come back until these markets are up 30 to 50 percent.”
This is a familiar situation for emerging-market investors. After crises occur, markets and currencies decline. Eventually, a turning point is reached. But the overall perception that the markets are down prevents investors from noticing when that point emerges.
“If you drop from 10 to 1 and then move back up to 2, that’s of course a 100 percent increase,” Mobius says. “But people don’t notice because of a perception the markets are down.”
Mobius notes that this cycle is the essential irony of emerging markets: that incredible volatility in individual countries creates the necessary conditions for specific opportunities, but monitoring that volatility can be quite stressful. To combat this, many investors focus not just on inexpensively priced companies but also on those where investors themselves can have an impact on management.
If you drop from 10 to 1 and then move back up to 2, that’s of course a 100 percent increase. But people don’t notice because of a perception the markets are down.
— Dr. Mark Mobius
Founder, Mobius Capital Partners
“Volatility is the new reality,” says Siobhan Morden, head of Latin America fixed income strategy for Nomura Securities International. She adds that the volatility of 2018 makes it difficult to talk about stability with conviction. “Emerging markets have essentially been stress-tested and are now focused on addressing those weaknesses. Risk-reward for emerging markets is much better and, broadly speaking, the bias is shifting toward a rally heading into 2019.”
China: Will trade friction escalate?
“China is at the top of everyone’s question list,” says Man Wing Chung, investment director at Value Partners Ltd., underscoring what many analysts believe is a key to managing expectations for 2019.
More to the point, threat of a U.S.-China trade war has resulted in the IMF reducing its global growth estimates from 3.9 to 3.7 percent for 2019. At the same time, the Chinese economy has slowed somewhat and inflation may rise along with consumption and wages. Managing portfolio exposure in this environment will likely require a bottom-up approach, focusing on companies that manage to sustain and even improve profitability by exploiting new business models and technology.
“Ultimately, a portfolio consists of companies,” says Gary Greenberg, head of emerging markets for Hermes. “There is no shortage of companies in emerging markets and Asia in particular with decent growth, good profitability and solid management.” From a valuation standpoint, these include Chinese insurers, consumer companies and technology companies, especially those involved in telecom and the rise of 5G networks.
Mobius agrees that the trade war threat, as well as ongoing deleveraging in China, are creating “winners and losers,” noting that “many Chinese companies are well positioned with respect to the currency and have already moved manufacturing out of China.”
One bright spot for investors is robust global acceptance of the yuan. While it depreciated by more than 8 percent in the second and third quarters, it was buoyed by demand outside of China. Overseas deposits rose to 1.086 trillion yuan this year, the currency was added to the IMF’s special drawing rights basket and the U.S. declined to label China a currency manipulator.
Together, all of these factors should make markets more comfortable with emerging-market risk.
Brazil: How will Bolsonaro govern?
Gauging political risks remains the top issue with Brazil, where right-wing Jair Bolsonaro won the presidential election in late October. He ran as an outsider candidate committed to pension reform and privatizing “everything from lender Banco do Brasil to oil company Petróleo Brasileiro SA,” according to his Finance Minister Paulo Guedes. Right now, Bolsonaro has a great deal of momentum. What remains to be seen is how he will actually govern.
“There are two criteria to look at,” Morden says. “Will he delegate to his very competent economic adviser and will he negotiate with congress? There are a lot of independent parties emerging he could build a coalition with. He has said he will not work with major parties or engage in patronage politics. That is easy to say when you’re running, but in office you have to be much more practical.”
The markets clearly want pension reform. Without stabilizing the fiscal deficit, it will be difficult to stabilize overall debt dynamics, which remain the country’s main credit weakness.
“Bolsonaro’s win is a shock similar to a Trump win,” Mobius adds. “Investors are looking at the possibility of more rule of law, more stability. That’s what he represents. As always, there will be winners and losers, so look at which companies will be impacted.”
Saudi Arabia: Will the transition continue?
Due to rising enthusiasm for electric vehicles and worldwide plans to ban gas-powered vehicles, there could be as many as 125 million electric vehicles on the road by 2030. Even so, that is a relatively small percentage of the world’s two billion cars. As a result, oil prices are returning and could even hit $100 again relatively soon.
This is good news for Saudi Arabia, which is struggling to wean itself from oil revenue as it manages a transition from a conservative, isolate and tradition-driven society to one that aligns better with the expectations of the modern world.
Changes in 2018 were noticeable, including the lifting of a ban on women drivers and greater tolerance for secular entertainment. But the country is also in the spotlight for the continuing war in Yemen and the killing of a journalist, both of which have complicated the nation’s relationship with the U.S. and the U.K.
With the world’s largest petroleum fields and $500 billion in foreign reserves, Saudi Arabia can rely on oil money for a long time. But the clock will run out at some point. It is unclear whether the country can retool its economy and create enough jobs in time, considering its 30 percent youth unemployment rate, a population half of which is 25 or younger and a workforce expected to double by 2030.
Nevertheless, the nation’s Vision 2030 plan is ambitious and aggressive, pouring funding into the education, health care and tourism sectors and even devoting $500 billion to build a futuristic megacity on the Red Sea coast to be called Neom.
Mexico: Battle of the acronyms
In the near term, the outlook for Mexico hinges on whether the United States-Mexico-Canada-Agreement (USMCA) will actually replace NAFTA. The stakes are high. Together, these three countries represent nearly 1.2 trillion in annual trade. Yet there are doubts about implementation as President Trump is expected to encounter resistance from the Democratic Party-controlled House of Representatives. In fact, toward the end of 2018, he threatened to terminate NAFTA altogether.
“Concerns surrounding the passage of USMCA are weighing on private investment,” says Damian Sassower, chief emerging markets credit strategist at Bloomberg Intelligence. “Behind the scenes, NAFTA has served as a safety blanket during negotiations. If Trump terminates the current agreement, it will dial up pressure on Congress to pass USMCA. Terminating NAFTA appears unlikely, but as the impasse regarding Trump’s proposed border wall grows, you can’t disregard any possibility.”
Sassower is also assessing the spending plans of new Mexican president, Andrés Manuel López Obrador (“AMLO”). AMLO campaigned on boosting wages, which requires funding that is unlikely to materialize, meaning wider deficits and slower GDP, perhaps dropping from 2.2 to 2.1 percent.
Which emerging market do you think has the most potential for growth in 2019?
- Saudi Arabia
“The new administration must acknowledge the fiscal limits of economic policy in Mexico,” Sassower says. “Despite AMLO’s lofty expectations, we need to see that he can work within the constraints of the current system. Access to foreign capital is critical as Mexico and state-owned oil producer Pemex rely heavily on external credit. AMLO has openly expressed opposition to the liberalization of Mexico’s energy market, so we need more color to understand how the end of the Pemex oil monopoly will unfold.”
The case for optimism
Despite all of the volatility past and present, the outlook for emerging markets looks positive in terms of corporate fundamentals.
“The market is saying the future is going to be a lot worse than the present, that 2019 is going to be a terrible year,” Greenberg says. “We’re not seeing that. With the companies we talk to,
revenues are growing, balance sheets are good and profitability is decent. Mobius concurs with this assessment. “Be optimistic,” he says. “I always tell people the world belongs to optimists.”
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Investing in China: A realistic approach for 2019
China remains a compelling prospect for the buy side, one that is enormous in scale and complexity.
Financial market reforms and openings continue to speed ahead. The bond, equity and foreign exchange markets are growing, presenting more opportunities for global investors. All of which may be why last summer, 40 percent of attendees at a Bloomberg buy-side conference indicated they are “more likely” to invest in emerging markets or North Asia in the next 12 months.
Will the trade war end or escalate?
Hanging over China’s investment prospects, however, is the uncertainty of the ongoing trade war with the U.S. An agreement between the two nations to reduce trade tensions is a positive sign for China’s growth, but it is not yet clear that its economy is out of the woods.
China total trade in 2018 by country
“The short-term outlook for 2019 is not especially great,” says Chang Shu, chief Asia economist for Bloomberg Economics. “The domestic economy is declining. The trade war is creating a lot of uncertainty. If there is more external pressure, the government will crank up investment, potentially generating more debt and creating more financial risks in the medium term. If trade tension eases, we may still see some slowdown but better overall composition of growth.”
Shu describes three potential scenarios for how the trade situation could affect China’s growth.
The first is true de-escalation, which could lead to China’s growth slowing to 6.3 percent from 6.6 percent for 2018, while exports slow slightly to 7 percent growth (down from 13.7 percent in 2018) and investment increasing 8.2 percent. The second scenario assumes the U.S. tariff rates rise to 25 percent in March, with growth slowing to 6.2 percent, exports declining by 3.9 percent and investment rising 11.1 percent. The third (and most unlikely) scenario assumes even higher tariffs on a wider range of imports, a situation in which growth slumps to 5.9 percent.
China economic forecast table
Domestically, Shu sees other risks, pointing out that many of the country’s key long-term policy goals — such as deleveraging, environmental regulation and control of government financing — involve growth trade-offs.
“Supporting growth without abandoning deleveraging and reforms is a lot harder to pull off than another major stimulus,” she says. “With leaders reluctant to give up hard-won progress necessary to sustain the economy in the medium term, stabilization in growth could take longer.”
Given these dynamics, how should the buy side evaluate opportunities in China in 2019? Is it fundamentally different from other geographies, or should asset managers still go sector by sector, company by company, security by security?
“Overall, China is quite similar to many other emerging markets in its patterns,” Shu says. “What makes it different is its size. If your risk is at a one in other emerging markets, for example, that risk will have a much larger multiplier in China.”
Shu notes there is a definite push and pull of financial opening followed by the government’s doubts about the opening, leading to constant swings in policy. She points to exchange rates to illustrate this idea. When the yuan declined recently, for example, the People’s Bank of China (PBOC) implemented a number of tools reminiscent of a time when it had much more stringent control, including stronger daily fixing rates, regulatory measures and window guidance.
“This helped the yuan, but with a slowing economy, potential trade war and generally negative sentiment about emerging markets, the downward pressure is likely to persist,” Shu says. “In other words, the PBOC may need to keep using this old playbook, which means its longer-term goal of capital account liberalization will get pushed to the back burner.”
While leadership has been making pro-growth changes since last June, macro data indicates the impact hasn’t yet arrived. Anecdotal evidence suggests the same — that private companies aren’t feeling much support from new policies yet. After a two-week trip to Beijing and Shanghai, Shu notes that private companies seem starved of funding and sentiment is weak.
“There’s a big risk that tight liquidity and poor sentiment deter private investment, dragging down growth and worsening the mix,” she says. “Tackling those challenges is crucial to re-energizing the private sector. The payoff would be stronger growth and a recovery that’s more balanced, with less reliance on government-led infrastructure spending and associated debt.”
During her trip, Shu encountered small and medium-sized private companies under stress due to tight liquidity in both traditional segments, such as footwear, as well as new ones, such as medical services. Cut off by trust companies, these firms are having real trouble finding alternative sources of funding. More to the point, assets in the shadow banking sector declined by 3 trillion yuan from a peak at the start of 2018, pain that is felt primarily by smaller private firms — a fact that is spreading pessimism across the private sector according to the firms Shu spoke with.
This is not to say that 2019 lacks opportunity. Shu feels positive about the Chinese insurance sector heading into 2019, along with construction, construction materials, transportation and related companies, because the government will likely continue to support infrastructure projects. Technology companies are another potential bright spot, including manufacturers as well as those developing new applications, such as AI in entertainment.
“Overall, there are positive developments in China,” Shu says. “The more the equity and bond markets grow, the more the country opens to global investors, the more promise there is for more efficient allocation of capital. But there is still a long road ahead.”
Looking even further ahead than 2019, Shu and her team at Bloomberg Economics estimate that Chinese stocks held by foreign investors could grow six times by 2025, and bonds close to 16 times.
“These estimates reflect forecasts for what China could achieve if reform and opening stay on track and there’s no significant setback in growth,” she says. “Critical to this success is a consistent approach that alleviates fears of sudden policy reversals.”
What is your top concern over investing in China's bond markets?
- Credit risk, such as rising corporate defaults
- Liquidity issues
- Local credit-rating discrepancy
- Lack of hedging tools
- Operational issues, such as language, trading hours, taxation etc
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Green bonds: Is sustainable investing sustainable?
The green bond market turned 10 in 2018.
These fast-growing investments had less than $1 billion in issuance when they arrived in 2008 but quickly gained momentum, finishing their first decade with exponential growth in 2016 followed by more than $170 billion issued in 2017.
As a result, many predicted another record year for green bonds in 2018, but gains were modest. Bloomberg Intelligence saw issuance rise from $125 billion in 2017 to $130 billion in 2018. The question the buy side needs answered is whether this easing is a pause in the action or the start of a longer plateau.
Green bond basics
Green bonds are pegged to a specific environmental or sustainability goal. They typically finance projects for environmentally friendly infrastructure, energy efficiency and clean energy, allowing issuers to reach investors with specific environmental concerns and giving buyers a way to fulfill mandates for socially responsible investments.
A quick snapshot of the market: The three major regions for green bond issuance are Europe, the U.S. and Asia-Pacific. Most green bonds are euro-denominated, representing an equivalent of $157 billion, or 43 percent of outstanding green bonds worldwide, while 24 percent are dollar-denominated and 17 percent are yuan-denominated. Interestingly, most green bonds held by investment managers are dollar-denominated — $18.2 billion, or 42 percent of the amount managed — which may be due to better liquidity. Evidence also suggests green bonds denominated in dollars trade at a noticeable premium compared with regular bonds vs. euro-denominated securities.
Of course, green bonds still represent a very small portion of the fixed income market — about half a percent of all issues in 2018. For the sake of comparison, the U.S. issued approximately $8 trillion in new debt securities in 2017.
Green bond issuance by country ($bn)*
Understanding the slowdown
Slower growth in 2018 is due primarily to a $27.5 billion decline in run rate by Chinese and French issuers. New entrants are active, including aggregate offerings of $11.9 billion by issuers in Belgium, Ireland, Indonesia, Luxembourg and Portugal. These new contributions would look more significant, however, without the massive
$16 billion (equivalent) issue by France in 2017. Without that single issue, new entrants would have easily offset the Chinese and French decline.
*This figure captures the issuance of green bonds as defined and recorded by Bloomberg Intelligence.
At the same time, growth in issuance from outside the traditional base of countries (China, France, the U.S., Germany and Sweden) is strong, representing nearly 50 percent of the green bond market. This share is up from just 24 percent in 2016.
Short break or permanent vacation?
Here are five factors to watch for in 2019 to help determine whether the green bond market will return to its recent strong growth trend.
1. More global issuers. Continued growth in the number of issuers could signify that the market’s longer-term growth trend remains strong. New issuers like Belgium and Ireland will need to continue to come to the market, picking up the slack in what could be a permanent slowdown in Chinese offerings. Right now, the breadth of the issuer base is indeed growing. Investors can select from 10 out of 11 industry sectors in 45 countries. Issuers of over $100 million reached 314 last year, up from 236 in 2017 and 134 in 2016.
2. Consistent labeling. If the 2018 decline in Chinese green bond offerings points toward a longer downturn, it may indicate investors are becoming wary of whether some green bonds are truly green. China, for example, still uses these bonds to back “clean coal” projects, drawing criticism from environmental activists. This problem is not unique to China. The Climate Bonds Initiative is a de facto gatekeeper for the market, offering the option for green bond issuers to verify adherence to their principles. But many issuers choose not to and they are under no obligation to ensure that their projects meet specific standards for environmental impact. The lack of consistent classification criteria is also why different research providers have varying estimates for annual issuance.
3. More government issuance. For green bonds to move from the billions to the trillions, governments in Europe, the U.S. and Asia-Pacific will need to intervene. Generally speaking, there are three paths to follow: incentivizing growth, mandating growth or leading by example. If governments step up, green bonds could follow a path similar to that of clean energy a decade ago. At that time, governments used these same strategies, including subsidies and minimum renewable energy sales requirements of utilities, to help the market thrive.
4. U.S. utilities come on strong. One reason
why the U.S. lags behind European countries in green bonds is the lack of issuance by non-municipal government agencies. Utilities dominate corporate green bonds in the U.S. and Europe, representing nearly 40 percent of total issuance. But while the total amount of utility bonds outstanding is equivalent (just under
$570 billion), these bonds account for 8 percent of the market in Western Europe — but only 1.4 percent in the U.S.
5. No European slowdown. Market maturity combined with wider volatility may suppress growth in euro green-bond sales, following two years during which issuance more than tripled. At the same time, other green financing options, including loans or securitizations, may get more attention. Together, all of these factors could make it difficult for European green bonds to maintain their pace of growth in 2019.
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The rise of passive funds: How far can they go?
Right now, passive mutual funds and exchange-traded funds (ETFs) that buy U.S. equities hold 48 percent of assets and are expected to top 50 percent soon. It’s a dramatic rise for passive investments, which represented only 20 percent of retail equity flows as recently as 2007. These trends hold globally. In Asia, 47.6 percent of assets are in passive equity funds. In Europe, index funds have grown from 13.2 percent of equity AUM in 2007 to a third of equity AUM in 2018.
It is clear why passive funds are seeing such strong growth. They typically offer more transparency and far lower fees than active funds. They have tax advantages, using buy-and-hold strategies that minimize capital gains taxes. They can also quickly capitalize on sectors with trending appeal, such as cannabis, vegan food or video games, which active funds can’t replicate as easily.
Most critically, passives have delivered better returns due to strong U.S. equity market performance. Passives are designed to match the market, whereas large-cap funds failed to outperform the S&P 500 benchmark more than 92 percent of the time from 2001 to 2016. Mid- and small-cap funds did even worse, and even large-cap value funds did not hit their benchmark 78.5 percent of the time.
As a result, retail and institutional investors alike have enthusiastically embraced passives. This is not welcome news for the buy side, for a variety of reasons. Increased passive AUM delivers limited revenue to asset managers. Passive assets represented $16 trillion in total, or 20 percent of all AUM in 2017, but produced revenues of just $17 billion, or 6 percent of the industry total. On top of this, active fund managers are under more pressure to lower fees, reducing revenues even further.
Active vs Passive ETF flows based in USD (US market only)
Obstacles to passives
Like all other investments, passives have shortcomings. Keep in mind that while passive funds are adding market share, their flows for 2018 fell short of their record-setting contributions of $700 billion in 2017.
One potential drag on passives is increased competition — spurred by their popularity — in a space where it is difficult to differentiate except by reducing prices. Fees for passives are already very low, but PwC predicts they will go lower, declining 20 percent or more to reach 0.12 percent by 2025. In fact, some passive managers have dropped their fees to zero to ward off competition. This does not mean fees are disappearing. Rather, zero-fee funds may be used to attract investors and then cross-sell other products and services, including active strategies in ETF wrappers that do have fees. These dynamics give an advantage to larger players that can scale enough to reduce margins and still maintain profitability.
Another potential barrier for passives is the risk of becoming top-heavy because most index funds are market-cap-weighted. This well-known risk has given rise to a subgroup of passives called smart beta.
The threat of smart beta
Smart beta mutual funds and ETFs combine passive index tracking with an active, rules-based component that increases diversification by weighting on specific factors such as value, growth or momentum.
Smart beta is still a relatively small category with $430 billion in AUM or 0.5 percent of the global total. But it has grown 30 percent a year since 2012 and Boston Consulting Group believes these products “pose a substantial threat to traditional active players—potentially even greater than that of the overall shift to passives.” The reason: smart beta attempts to produce active management results at lower costs.
The smart beta space itself is growing in diversity with the introduction of multi-factor funds, which offer exposure to more than one factor. Adding to the complexity is the reality that not all funds define factors in exactly the same way.
“What I like about factor funds is they are rule-based, so you know exactly how they are constructed and rebalanced,” says Lars Kalbreier, CIO, Vontobel Wealth Management. “Having said that, if you use the name ‘value’ you will see people have different understandings of what value is. It’s very important not to buy any value ETF or value index fund without looking at how it is built. You will see big discrepancies in value products.”
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Another issue that affects smart beta growth is the split between “authentic” or “pure” factor ETFs that use academic research, concentrated portfolios, high turnover and, at times, short positions and “watered-down” factor ETFs that dilute factors so much that they deliver market returns. So-called watered-down funds took in $55 billion over the past three years while “pure” value ETFs had almost no inflows.
Vitali Kalesnik, partner, Research Affiliates, explains the difference between pure and watered-down funds with an interesting analogy.
“The difference in these vehicles is like the difference between a motorcycle and a train,” he says. “The motorcycle is a nimble vehicle, and if you know what you’re doing, you can move very quickly from one place to another. But a train is going to be cheaper and more reliable. If you don’t know how to use it, it won’t hurt you. Most people prefer the train.”
Is passive domination inevitable?
Passives overtaking actives is not a given. This isn’t the first time passives were predicted to reach a tipping point. Trends in 2017 pointed to 2018 as the year passives would take over, but it didn’t happen. The end of the bull market in the U.S., should it arrive in 2019, could hamper passive growth. One thing is clear: given the rapidly evolving relationships among passives, actives and smart beta products that fall somewhere in between, the story is likely more complex than a simple choice between one approach or the other.
AI: Five trends to watch in 2019
Will AI completely transform the industry in the next five years?
Or is it just another tool that will help financial professionals make better decisions more efficiently? Here, experts from across the AI field identify five trends in AI for the coming year.
1. Identifying best execution
Most buy-side professionals want to know how AI can assist with alpha generation, according to Matthew Sargaison, co-chief executive officer of Man AHL. But Sargaison believes AI could make a bigger impact much sooner on the execution side. Not only can AI deliver better modeling of the order book to improve execution, it can also use reinforcement learning to optimize order routing.
“Rather than classic A/B testing, AI can perform tests that are much more dynamic,” he says. “Every time they trade, AI tools learn more about how to execute trades for a given model. Over time, they figure out the best distribution. This delivers optimal results and frees up humans to do more productive work than making these calculations.”
2. Predicting trade failure
The predictive power of AI isn’t just hype, according to Thomas Durif, global head of middle office and data products for BNP Paribas Securities Services. Right now, tools are emerging that can predict whether a trade will fail within a three-day window after it is made.
Trades fail for a variety of reasons that can be difficult to predict. New AI tools analyze historical data to identify patterns of trades that have previously failed and alert asset managers and brokers when similar conditions occur, so they can take action sooner.
“With AI, we can see problems with trades before they happen,” he says. “This application is very much in line with the broader regulatory effort to impose fines for trade failures.”
3. Advanced decision support
Jeremy Waite, chief strategy officer for IBM Watson Customer Engagement in Europe, thinks a forthcoming AI system capable of debating humans on complicated topics could revolutionize decision support in finance and other industries.
“It can handle arguments without binary answers,” he says. “As a result, it’s capable of helping people make insightful decisions that have huge implications.”
The reason this is important for financial professionals, Waite notes, is the constant need to make sense of escalating volumes of data. Out of all the data that exists at this moment, 90 percent was created in the last 12 months and 80 percent is unstructured, including social media data, voice data and data from connected devices in the Internet of Things.
“Humans can’t keep up,” Waite says. “Only about
a third of that data is useful. AI can help you find the data that is actually of value and gain insights from it.”
4. Automated portfolio management
One of the biggest concerns about AI is that it could replace humans in the workplace. Sargaison, for example, maintains that increased automation has actually given asset managers the freedom to hire larger teams focused on creative research that only humans can perform.
Marco Fasoli, co-chief executive officer and co-founder for A.I. Machines, however, offers a much more provocative point of view. He describes AI tools already in use today that replicate the entire investment process — including data processing and analysis, trading idea generation, risk management and the determination of optimal portfolio weights — and that can be applied to any portfolio management system as long as the underlying assets are liquid.
“This industry will be completely transformed within five years whether we like it or not,” Fasoli says. “There are already 100 percent AI-powered products that can give you a slight predictive edge on both risk and price. It’s not a silver bullet, of course. But that edge, embedded in the right software framework, can deliver substantially improved investment outcomes.”
5. Integrating ethics
Can algorithms learn to be ethical? This is just one question that concerns Catalina Butnaru, an ambassador for City AI and Women in AI in London, whose work focuses on integrating ethical thinking into product design.
In finance, integrating ethics means ensuring that the personal perspectives of data scientists and other experts do not inform how AI algorithms are trained, developed or used. Data scientists, understandably, tend to optimize for error rate, prediction speed and other measurable KPIs and not focus on more complicated, non-measurable issues, such as the well-being of humanity.
“There could be a risk of having one expert influence what you measure, and that person could be intrinsically biased,” she says. “If you only measure performance KPIs, you may become over-optimized. Is that the only thing you should focus on? And is that the right thing to do?”
Butnaru believes ethical alignment should happen at the product design level, guided by an “ethics team” made up of, for example, a data scientist, a project manager and someone who brings a perspective from outside the business.
“You can’t solve the problem of ethical misalignment by developing better algos,” she says. “It’s a mathematical sequence. It can’t be more or less ethical. You have to prioritize ethics as much as you prioritize other performance indicators. That’s important for reducing reputational risk.”
Machine learning: Finding clear signals in a noisy market
Week by week, the financial industry gains access to higher volumes of data.
This data, both structured and unstructured, comes from traditional and alternative sources. The buy side’s overriding concern is whether or not these increasingly large and complex data sets can help predict market behavior. The answer lies in machine learning, according to Bruno Dupire, head of quantitative research at Bloomberg.
“It’s natural to use machine learning as opposed to classical statistical methods, even if conceptually they are not very different,” Dupire says. “In one sense, machine learning is just advanced statistics. Both are trying to extract the signal from the noise. And, in finance, there is always a lot of noise.”
Dupire notes that while these methods do share commonalities, machine learning has a unique ability to systematically exploit nonlinearities — or relationships in which the output does not change in proportion to a change in the inputs.
Specifically, machine learning uses much higher dimension representations of data than is possible with the standard statistical toolkit. Machine learning can help make sense of vast amounts of unstructured data by mapping it into a numerical format that is more amenable to algorithmic analysis. Many examples of this are by now familiar, including forecasting based on light intensity in a city or the number of cars in a retailer’s parking lot.
One example of how machine learning can process unstructured data is sentiment analysis of news articles and social media posts. This is not a deep syntactic analysis, Dupire explains, but rather an automatic mapping of text in terms of its probability of being positive, neutral or negative. The algorithm is “trained” how to do this with a large set of text that people have already classified correctly. Using support vector machine (SVM), long short-term memory (LSTM) and many other techniques, Dupire and his team observe and correct the algorithm’s ability to detect sentiment.
“Once the algorithm is tuned, we let it analyze live tweets,” Dupire says. “The way this is used on the Bloomberg Terminal service is the social velocity function, which can analyze the sentiment for a stock in five-minute increments.”
This kind of supervised learning can also be applied to exotic option pricing. In this scenario, the goal is to teach the algorithm to understand the deterministic relationship between various deal parameters and the price of the option. Because these deterministic functions are very complex, each price evaluation can be extremely time-consuming. This is where machine learning lends an advantage, because the algorithm can be trained on examples of prices generated from a wide variety of market situations and deal parameters.
“Once you have a database of actual prices, you can generate a pricing function that can be applied to conditions and parameters the algorithm hasn’t seen before,” Dupire says. “If you have pre-computed a rich set of data, the interpolation method can be quite fast to price new deals.”
In terms of structured data, machine learning can be immensely helpful in filtering out broader market effects to understand the behavior of a single security. Within Dupire’s group, this effort is called Project 499 because it attempts to estimate the returns of one stock in the S&P 500 based on information about the remaining 499.
“If a stock you are interested in loses 4 percent on a given day but the market was down by 3 percent, that information is not really informative,” he says. “To understand what’s happening, you need to mute the influence of global factors that affect the market or sector as a whole.”
For example, a stock price is generally understood to drop by the amount of the dividend at the
ex-date. But the dividend yield is typically 0.5 percent per quarter, which is less than a stock’s daily movement. In other words, if you want to know whether the market is reacting correctly to the ex-date, looking at the time series will not be of much value.
“We’re observing the real return of one stock and comparing it with our best estimate based on what we know about the others,” Dupire says. “The difference constitutes the surprise, which is the quantity we are interested in. With machine learning, we can systematically filter out other factors, get a purified time series, kill a lot of the noise and get a much cleaner analysis.”
Factor-based strategies are an excellent fit for machine learning. The number of factors to consider is extensive, ranging from classical elements such as P/E ratio and long-term debt to supply chain data to option data from volatility surfaces. Machine learning can help determine the best possible combination of factors faster and with greater flexibility.
“Machine learning helps us use any available information and exploit it to see if there is a combination of factors that will allow us to better explain future returns,” Dupire says. “In this case, the inputs are all of these characteristics of the stock and the output is future performance.”
No matter what factors you want to consider, the steps in the process are the same. First, you define your universe of stocks, whether that is companies with high diversity or low volatility. Then you choose the characteristics to combine into a composite factor and apply filters to select a sub-universe of stocks to consider for investment. Machine learning accelerates the process so that it is much easier to apply grouping and sorting tools, normalize volatility of various groups, risk-equalize different factors and see where changes in value are distributed to various sectors.
Another practical application of machine learning is identifying which strategies will work best according to market conditions. This is a similar concept to Project 499, because you can select any number of factors to describe the state of the market, find periods in the past that correspond to these factors, and analyze which strategies worked well during these periods. Essentially, the algorithm informs you how to rotate through various strategies as market conditions evolve.
However, Dupire cautions that the rules of the market tend to change quickly and that the market itself is a machine “made to destroy signals.”
“When we talk about factor investing, everyone is trying to find a new characteristic that may have some predictive powers,” he says. “Every time you discern a signal that is exploitable, it’s likely you’re not the only one. To discover these opportunities and act on them, you need the proper tools. That’s what we are trying to do with machine learning.”
Data volumes and complexity will only grow as more market participants understand and appreciate the vast web of interconnectivity that defines much of the financial world. Each of these connection points could be transformed into fuel for forecasting with the help of machine learning. At the same time, advances in analytical techniques, combined with continuously improving computing power, are expanding the practical applications of this exciting technology even further.
Which alternative data are you most keen to adopt?
- Foundational company level (e.g., ESG, supply chain)
- Sentiment (e.g.,filing insights, trader sentiment)
- Consumer (e.g.,mall foot traffic, social media)
- Economics (e.g.,geopolitical risk predictive analytics)
Financial firms are increasingly using previously cumbersome, inconsistent, non-traditional data to inform their investment decisions and risk management strategies. While firms recognize the value of newer datasets for alpha generation, they face challenges like data connectivity, varying quality and ease-of-use. By offering clients a singular access point for finding and receiving reliable data, alternative and otherwise, Bloomberg reduces operational aspects of the data procurement processes, speeding up time to value and enabling easy integration to existing systems.
Learn more about Bloomberg's Enterprise Data and alternative data solution.
Where will the buy side be in five years?
The buy side finds itself at a transitional moment.
After 2016 saw the first decline in global revenues and profits since the 2008 crisis, 2017 rebounded with record-breaking performance backed by bull markets. This momentum carried into 2018. In fact, Edouard Leveque, head of Bloomberg buy-side order manageament sales in EMEA, notes that the asset management industry has a CAGR hovering between 6 and 7 percent and remains on track to exceed $120 trillion by 2020.
At the same time, margins are under extreme pressure, especially for firms in the middle of the AUM spectrum; this margin pressure will only become more challenging when strong equity markets eventually slow down. The nature of the industry is shifting as net flows to core active management are expected to decrease 8 percent during the next two years, with inflows favoring non-core investment strategies such as passives, ETFs, specialties and alternatives.
All of this may be why, on the back of its annual benchmark survey of leading asset managers, Boston Consulting Group sees 2018 as an “inflection point” in the industry’s ongoing transformation. The group predicts that in five years, asset managers will look very different than they do today due to a combination of structural shifts in the market and digital innovation.
They further predict that to succeed, firms will need to make profound changes in their technology. This makes intuitive sense. By increasing operational efficiency, or “doing more with less,” firms can ease margin pressures. This often starts with a broader effort to optimize the target operating model (TOM) — including how it is organized, how it processes data and how it utilizes technology. BCG notes that asset managers that optimize their TOM can expect cost savings of 10 to 20 percent.
The challenge, however, is what comes next. Once the TOM is optimized, where do asset managers invest in technology? Just as not every firm has the same business model, not every firm needs to adopt the same solutions. Setting priorities will likely depend on which buy-side trends affect your business the most.
Firms that have addressed operational efficiency still find themselves in a difficult environment for alpha generation. To stand out from competitors, asset managers should consider investing in cutting-edge technologies, including artificial intelligence (AI) and machine learning (ML), to uncover opportunities, process more structured and unstructured data, and potentially gain an edge in predicting risk and price. Another way to differentiate is through specialization, which means asset managers should focus on technologies that provide advantages in niche markets. Of course, buy-side firms could choose both, using AI and ML to strengthen offerings in specialized regions, sectors or asset classes.
Data and analytics
The BCG survey says that most asset managers are pursuing digital strategies, whether that involves new analytics, digital labs, hiring data scientists or exploring alternative data sets. Much of this is designed to demonstrate value to clients that are quickly realizing the transformative power of data. Investing in new analytics technology can give asset managers a way to make data-driven recommendations based on a specific client’s history, thus allowing firms to couple stronger investment performance with value that exceeds clients’ basic expectations.
Active vs. passive
The “race to zero” in passives makes fees in active funds look even higher by comparison. In an environment where passive funds continue to see strong flows and outperform actives due to strong equity market performance, active managers should invest in technology that reduces costs and allows greater operational efficiency. As we will see in the following case study, trade automation is an increasingly popular choice, as are data management solutions that eliminate redundancies in data import, cleansing, distribution and consumption, as well as tools that predict trade failures.
The journey continues
The technology and data transformation journey is never truly complete. All organizations evolve, so operating models must change, too. But this journey has to start somewhere. Otherwise, firms will continue to rely on fragmented systems, inconsistent data and inefficient operations. Buy-side leaders understand this isn’t an option. They know that remaining competitive means establishing a future operating model, leveraging data as a strategic asset and partnering with an experienced buy-side technology provider that can help them implement their TOM effectively.
Bloomberg’s trade execution and order management solutions provide multi-asset order and execution management solutions and investment cycle analytics that enable buy-side firms to turn their trade and order data into a competitive advantage. As a result, firms can create more efficient workflows, connect to the global capital markets, drive regulatory compliance and lower their total cost of ownership. Learn more.
Case study: trade automation
As just one example of how the buy side is adopting new technology, consider the appeal
of trade automation. These products are designed to help execution traders boost productivity, managing more orders during the daily trading window, as well as separating incoming order
flow into “high-touch” and “low-touch” functions.
Low-touch orders are those in liquid benchmark products, such as on-the-run USTs, while high-touch orders are larger in size and involve
difficult-to-find names, such as a high-yield corporate where the PM wants to discretely trade in block size.
“Forward-thinking traders understand automation is not a threat,” says Ravi Sawhney, global head of trade automation at Bloomberg. “The idea is, how can we free up the bandwidth of the human trader to focus on more profitable activities? It makes traders more productive if they spend their time on more complex orders while automation takes care of the rest.”
Sawhney adds that automation allows the desk to scale through technology, not just headcount. For example, assume that under conventional circumstances an asset manager with $1 billion AUM and 10 traders would need to add another 10 traders to double AUM. With the help of automation, however, the same asset manager could scale to $2 billion AUM but only need to add five traders, achieving a built-in competitive advantage.
Today, traders need access to fragmented pools of liquidity, an intuitive execution platform, automated analytics and workflows, as well as high-quality data.
Bloomberg's Electronic Trading Solutions help buy-side professionals strive to achieve best execution across multiple asset classes with advanced trading solutions and sophisticated analytics in one a single platform.
Learn more about Bloomberg's Fixed Income Trading.
What excites you the most about the future of buy-side technology?
- Richer analytics
- Increased automation
- Seamless workflows
- More investment methods
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